Dataset Information

Urbanization Impacts the Physicochemical Characteristics and Abundance of Fecal Markers and Bacterial Pathogens in Surface Water.

ABSTRACT: Urbanization is increasing worldwide and is happening at a rapid rate in China in line with economic development. Urbanization can lead to major changes in freshwater environments through multiple chemical and microbial contaminants. We assessed the impact of urbanization on physicochemical characteristics and microbial loading in canals in Suzhou, a city that has experienced rapid urbanization in recent decades. Nine sampling locations covering three urban intensity classes (high, medium and low) in Suzhou were selected for field studies and three locations in Huangshan (natural reserve) were included as pristine control locations. Water samples were collected for physicochemical, microbiological and molecular analyses. Compared to medium and low urbanization sites, there were statistically significant higher levels of nutrients and total and thermotolerant coliforms (or fecal coliforms) in highly urbanized locations. The effect of urbanization was also apparent in the abundances of human-associated fecal markers and bacterial pathogens in water samples from highly urbanized locations. These results correlated well with land use types and anthropogenic activities at the sampling sites. The overall results indicate that urbanization negatively impacts water quality, providing high levels of nutrients and a microbial load that includes fecal markers and pathogens.

SUBMITTER: Yuan T

PROVIDER: S-EPMC6572354 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Urbanization Impacts the Physicochemical Characteristics and Abundance of Fecal Markers and Bacterial Pathogens in Surface Water.

Yuan Tianma T Vadde Kiran Kumar KK Tonkin Jonathan D JD Wang Jianjun J Lu Jing J Zhang Zimeng Z Zhang Yixin Y McCarthy Alan J AJ Sekar Raju R

International journal of environmental research and public health 20190516 10

Urbanization is increasing worldwide and is happening at a rapid rate in China in line with economic development. Urbanization can lead to major changes in freshwater environments through multiple chemical and microbial contaminants. We assessed the impact of urbanization on physicochemical characteristics and microbial loading in canals in Suzhou, a city that has experienced rapid urbanization in recent decades. Nine sampling locations covering three urban intensity classes (high, medium and lo ...[more]

PMID: 31100947

Similar Datasets

Project description:To assess fecal pollution in coastal waters, current monitoring is reliant on culture-based enumeration of bacterial indicators, which does not account for the presence of viable but non-culturable or sediment-associated micro-organisms, preventing effective quantitative microbial risk assessment (QMRA). Seasonal variability in viable but non-culturable or sediment-associated bacteria challenge the use of fecal indicator organisms (FIOs) for water monitoring. We evaluated seasonal changes in FIOs and human enteric pathogen abundance in water and sediments from the Ribble and Conwy estuaries in the UK. Sediments possessed greater bacterial abundance than the overlying water column, however, key pathogenic species (Shigella spp., Campylobacter jejuni, Salmonella spp., hepatitis A virus, hepatitis E virus and norovirus GI and GII) were not detected in sediments. Salmonella was detected in low levels in the Conwy water in spring/summer and norovirus GII was detected in the Ribble water in winter. The abundance of E. coli and Enterococcus spp. quantified by culture-based methods, rarely matched the abundance of these species when measured by qPCR. The discrepancy between these methods was greatest in winter at both estuaries, due to low CFU's, coupled with higher gene copies (GC). Temperature accounted for 60% the variability in bacterial abundance in water in autumn, whilst in winter salinity explained 15% of the variance. Relationships between bacterial indicators/pathogens and physicochemical variables were inconsistent in sediments, no single indicator adequately described occurrence of all bacterial indicators/pathogens. However, important variables included grain size, porosity, clay content and concentrations of Zn, K, and Al. Sediments with greater organic matter content and lower porosity harbored a greater proportion of non-culturable bacteria (including dead cells and extracellular DNA) in winter. Here, we show the link between physicochemical variables and season which govern culturability of human enteric pathogens and FIOs. Therefore, knowledge of these factors is critical for accurate microbial risk assessment. Future water quality management strategies could be improved through monitoring sediment-associated bacteria and non-culturable bacteria. This could facilitate source apportionment of human enteric pathogens and FIOs and direct remedial action to improve water quality.

Project description:In this study, host-associated molecular markers and bacterial 16S rRNA gene community analysis using high-throughput sequencing were used to identify the sources of fecal pollution in environmental waters in Brisbane, Australia. A total of 92 fecal and composite wastewater samples were collected from different host groups (cat, cattle, dog, horse, human, and kangaroo), and 18 water samples were collected from six sites (BR1 to BR6) along the Brisbane River in Queensland, Australia. Bacterial communities in the fecal, wastewater, and river water samples were sequenced. Water samples were also tested for the presence of bird-associated (GFD), cattle-associated (CowM3), horse-associated, and human-associated (HF183) molecular markers, to provide multiple lines of evidence regarding the possible presence of fecal pollution associated with specific hosts. Among the 18 water samples tested, 83%, 33%, 17%, and 17% were real-time PCR positive for the GFD, HF183, CowM3, and horse markers, respectively. Among the potential sources of fecal pollution in water samples from the river, DNA sequencing tended to show relatively small contributions from wastewater treatment plants (up to 13% of sequence reads). Contributions from other animal sources were rarely detected and were very small (<3% of sequence reads). Source contributions determined via sequence analysis versus detection of molecular markers showed variable agreement. A lack of relationships among fecal indicator bacteria, host-associated molecular markers, and 16S rRNA gene community analysis data was also observed. Nonetheless, we show that bacterial community and host-associated molecular marker analyses can be combined to identify potential sources of fecal pollution in an urban river. This study is a proof of concept, and based on the results, we recommend using bacterial community analysis (where possible) along with PCR detection or quantification of host-associated molecular markers to provide information on the sources of fecal pollution in waterways.

Project description:Agricultural water is an important source of foodborne pathogens on produce farms. Managing water-associated risks does not lend itself to one-size-fits-all approaches due to the heterogeneous nature of freshwater environments. To improve our ability to develop location-specific risk management practices, a study was conducted in two produce-growing regions to (i) characterize the relationship between Escherichia coli levels and pathogen presence in agricultural water, and (ii) identify environmental factors associated with pathogen detection. Three AZ and six NY waterways were sampled longitudinally using 10-L grab samples (GS) and 24-h Moore swabs (MS). Regression showed that the likelihood of Salmonella detection (Odds Ratio [OR] = 2.18), and eaeA-stx codetection (OR = 6.49) was significantly greater for MS compared to GS, while the likelihood of detecting L. monocytogenes was not. Regression also showed that eaeA-stx codetection in AZ (OR = 50.2) and NY (OR = 18.4), and Salmonella detection in AZ (OR = 4.4) were significantly associated with E. coli levels, while Salmonella detection in NY was not. Random forest analysis indicated that interactions between environmental factors (e.g., rainfall, temperature, turbidity) (i) were associated with likelihood of pathogen detection and (ii) mediated the relationship between E. coli levels and likelihood of pathogen detection. Our findings suggest that (i) environmental heterogeneity, including interactions between factors, affects microbial water quality, and (ii) E. coli levels alone may not be a suitable indicator of food safety risks. Instead, targeted methods that utilize environmental and microbial data (e.g., models that use turbidity and E. coli levels to predict when there is a high or low risk of surface water being contaminated by pathogens) are needed to assess and mitigate the food safety risks associated with preharvest water use. By identifying environmental factors associated with an increased likelihood of detecting pathogens in agricultural water, this study provides information that (i) can be used to assess when pathogen contamination of agricultural water is likely to occur, and (ii) facilitate development of targeted interventions for individual water sources, providing an alternative to existing one-size-fits-all approaches.

Dataset Information

Urbanization Impacts the Physicochemical Characteristics and Abundance of Fecal Markers and Bacterial Pathogens in Surface Water.

Publications

Urbanization Impacts the Physicochemical Characteristics and Abundance of Fecal Markers and Bacterial Pathogens in Surface Water.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure